• 대한전기학회:학술대회논문집
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• 대한전기학회 2006년도 제37회 하계학술대회 논문집 D
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• pp.2113-2115
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• 2006

This paper proposes a spatio-temporal correlation algorithm that takes advantage of the spatial and temporal correlations in video streams for error concealment. The spatio-temporal correlation algorithm sets the neighborhood area of the damaged part as a reference window, then finds the area that best matches the reference window in the previous frame. The best-matched area in the previous frame replaces the damaged part in the current frame. The results of ten variations of the proposed algorithm are compared with conventional error concealment methods. These methods include the ones applicable to P-frames as well as I-frames. The comparison results show that the proposed algorithm is very efficient for l-frame error concealment with a large motion between frames.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제9권7호
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• pp.2488-2511
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• 2015

Data redundancy has high impact on Wireless Sensor Network's (WSN) performance and reliability. Spatial and temporal similarity is an inherent property of sensory data. By reducing this spatio-temporal data redundancy, substantial amount of nodal energy and bandwidth can be conserved. Most of the data gathering approaches use either temporal correlation or spatial correlation to minimize data redundancy. In Collective Prediction exploiting Spatio Temporal correlation (CoPeST), we exploit both the spatial and temporal correlation between sensory data. In the proposed work, the spatial redundancy of sensor data is reduced by similarity based sub clustering, where closely correlated sensor nodes are represented by a single representative node. The temporal redundancy is reduced by model based prediction approach, where only a subset of sensor data is transmitted and the rest is predicted. The proposed work reduces substantial amount of energy expensive communication, while maintaining the data within user define error threshold. Being a distributed approach, the proposed work is highly scalable. The work achieves up to 65% data reduction in a periodical data gathering system with an error tolerance of 0.6℃ on collected data.

• 한국수자원학회:학술대회논문집
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• 한국수자원학회 2016년도 학술발표회
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• pp.164-164
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• 2016

Radar rainfall estimates have been widely used in calculating rainfall amount approximately and predicting flood risks. The radar rainfall estimates have a number of error sources such as beam blockage and ground clutter hinder their applications to hydrological flood forecasting. Moreover, it has been reported in paper that those errors are inter-correlated spatially and temporally. Therefore, in the current study, we tested influence about spatio-temporal errors in radar rainfall estimates. Spatio-temporal errors were simulated through a stochastic simulation model, called Multivariate Autoregressive (MAR). For runoff simulation, the Nam River basin in South Korea was used with the distributed rainfall-runoff model, Vflo. The results indicated that spatio-temporal dependent errors caused much higher variations in peak discharge than spatial dependent errors. To further investigate the effect of the magnitude of time correlation among radar errors, different magnitudes of temporal correlations were employed during the rainfall-runoff simulation. The results indicated that strong correlation caused a higher variation in peak discharge. This concluded that the effects on reducing temporal and spatial correlation must be taken in addition to correcting the biases in radar rainfall estimates. Acknowledgements This research was supported by a grant from a Strategic Research Project (Development of Flood Warning and Snowfall Estimation Platform Using Hydrological Radars), which was funded by the Korea Institute of Construction Technology.

• 대한원격탐사학회지
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• 제37권5_1호
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• pp.999-1011
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• 2021

다중 센서 영상으로부터 공간 및 시간해상도가 모두 높은 영상을 예측하는 시공간 융합에서 다중 센서 영상의 방사학적 불일치는 예측 성능에 영향을 미칠 수 있다. 이 연구에서는 다중 센서 위성영상의 서로 다른 분광학적 특성을 보정하는 방사보정이 융합 결과에 미치는 영향을 분석하였다. 두 농경지에서 얻어진 Sentinel-2, PlanetScope 및 RapidEye 영상을 이용한 사례연구를 통해 상대 방사보정의 효과를 정량적으로 분석하였다. 사례연구 결과, 상대 방사보정을 적용한 다중 센서 영상을 사용하였을 때 융합의 예측 정확도가 향상되었다. 특히 입력 자료 간 상관성이 낮은 경우에 상대 방사보정에 의한 예측 정확도 향상이 두드러졌다. 분광 특성의 차이를 보이는 다중 센서 자료를 서로 유사하게 변환함으로써 예측 성능이 향상된 것으로 보인다. 이 결과를 통해 상대 방사보정은 상관성이 낮은 다중 센서 위성영상의 시공간 융합에서 예측 능력을 향상시키기 위해 필요할 것으로 판단된다.

• 한국군사과학기술학회지
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• 제14권5호
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• pp.913-919
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• 2011

In this paper, we present a new efficient event detection algorithm for sensor networks with faults. We focus on multi-attributed events, which are sets of data points that correspond to interesting or unusual patterns in the underlying phenomenon that the network monitors. Conventional algorithms cannot detect some events because they treat only their own sensor readings which can be affected easily by environmental or physical problem. Our approach exploits spatio-temporal correlation of sensor readings. Sensor nodes exchange a fault-tolerant code encoded their own readings with neighbors, organize virtual sensor readings which have spatio-temporal correlation, and determine a result for multi-attributed events from them. In the result, our proposed algorithm provides improvement of detecting multi-attributed events and reduces the number of false-negatives due to negative environmental effects.

• 한국환경과학회지
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• 제27권7호
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• pp.499-507
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• 2018

Agricultural meteorological information is an important resource that affects farmers' income, food security, and agricultural conditions. Thus, such data are used in various fields that are responsible for planning, enforcing, and evaluating agricultural policies. The meteorological information obtained from automatic weather observation systems operated by rural development agencies contains missing values owing to temporary mechanical or communication deficiencies. It is known that missing values lead to reduction in the reliability and validity of the model. In this study, the hierarchical Bayesian spatio-temporal model suggests replacements for missing values because the meteorological information includes spatio-temporal correlation. The prior distribution is very important in the Bayesian approach. However, we found a problem where the spatial decay parameter was not converged through the trace plot. A suitable spatial decay parameter, estimated on the bias of root-mean-square error (RMSE), which was determined to be the difference between the predicted and observed values. The latitude, longitude, and altitude were considered as covariates. The estimated spatial decay parameters were 0.041 and 0.039, for the spatio-temporal model with latitude and longitude and for latitude, longitude, and altitude, respectively. The posterior distributions were stable after the spatial decay parameter was fixed. root mean square error (RMSE), mean absolute error (MAE), mean absolute percentage error (MAPE), and bias were calculated for model validation. Finally, the missing values were generated using the independent Gaussian process model.

• 한국수산과학회지
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• 제56권4호
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• pp.558-568
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• 2023

The spatio-temporal distribution of the sand crab Ovalipes punctatus larvae was investigated in the Korean waters in 2019. Sea surface temperature (SST) was the lowest in February and highest in September. Sea surface salinity (SSS) was the lowest in September and highest in March. Further, sea surface chlorophyll a (SSC) was the highest in September. Larvae were distributed in the South Sea and coastal area of Jeju Island from April to June, and the abundance was the highest in May. The spatio-temporal distribution analysis suggested that larval groups showed a tendency to be dispersed over a wider area as the larvae developed, due to the increase in their swimming ability. The correlation analysis between environmental factors and larval density suggested that larvae appeared in the SST range 11.8-20.9℃ and SSS range 31.5-35.3 psu. The Megalopal stage appeared in a wider range of SST and SSS than other larval stages, possibly due to the increased environmental tolerance before settlement. Results of redundancy analysis (RDA) and Spearman's rank correlation analysis between the larval density by developmental stages and the environmental factors suggested that SST showed a positive correlation and SSC showed a negative correlation in the later stage.

• 대한원격탐사학회지
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• 제36권5_1호
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• pp.807-821
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• 2020

이 연구에서는 작물 모니터링을 위한 시계열 고해상도 영상 구축을 위해 기존 중저해상도 위성영상의 융합을 위해 개발된 대표적인 시공간 융합 모델의 적용성을 평가하였다. 특히 시공간 융합 모델의 원리를 고려하여 입력 영상 pair의 특성 차이에 따른 모델의 예측 성능을 비교하였다. 농경지에서 획득된 시계열 Sentinel-2 영상과 RapidEye 영상의 시공간 융합 실험을 통해 시공간 융합 모델의 예측 성능을 평가하였다. 시공간 융합 모델로는 Spatial and Temporal Adaptive Reflectance Fusion Model(STARFM), SParse-representation-based SpatioTemporal reflectance Fusion Model(SPSTFM)과 Flexible Spatiotemporal DAta Fusion(FSDAF) 모델을 적용하였다. 실험 결과, 세 시공간 융합 모델은 예측 오차와 공간 유사도 측면에서 서로 다른 예측 결과를 생성하였다. 그러나 모델 종류와 관계없이, 예측 시기와 영상 pair가 획득된 시기 사이의 시간 차이보다는 예측 시기의 저해상도 영상과 영상 pair의 상관성이 예측 능력 향상에 더 중요한 것으로 나타났다. 또한 작물 모니터링을 위해서는 오차 전파 문제를 완화할 수 있는 식생지수를 시공간 융합의 입력 자료로 사용해야 함을 확인하였다. 이러한 실험 결과는 작물 모니터링을 위한 시공간 융합에서 최적의 영상 pair 및 입력 자료 유형의 선택과 개선된 모델 개발의 기초정보로 활용될 수 있을 것으로 기대된다.

• 응용통계연구
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• 제25권2호
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• pp.351-362
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• 2012

일기 산출기 모형은 가상의 일기 자료를 생성하는 통계 모형이다. 본 연구는 시공간 상관성이 고려된 다중지점에서의 일기산출 모형을 제안하고, 온실가스 배출 미래 시나리오에 따라 강수량과 평균 기온 일기산출이 가능한 알고리즘을 개발하였다. 제안된 알고리즘은 다단계 일반화 선형모형 하에서 필요한 모수들을 추정하고, 적합된 모형 하에서 일기변수들을 랜덤하게 산출하는 절차이다. 과거 30년간 관측된 우리나라 4대강 유역의 일 강수량 자료와 평균 기온 자료를 가지고 모형을 적합하고, 미래 일별 일기자료 산출에 적용하였다.

• ETRI Journal
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• 제30권6호
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• pp.765-773
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• 2008

Spatial correlation is a result of insufficient antenna spacing among multiple antenna elements, while temporal correlation is caused by Doppler spread. This paper compares the effect of spatial and temporal correlation in order to investigate the performance of multiuser scheduling algorithms in multiple-input multiple-output (MIMO) broadcast channels. This comparison includes the effect on the ergodic capacity, on fairness among users, and on the sum-rate capacity of a multiuser scheduling algorithm utilizing statistical channel state information in spatio-temporally correlated MIMO broadcast channels. Numerical results demonstrate that temporal correlation is more meaningful than spatial correlation in view of the multiuser scheduling algorithm in MIMO broadcast channels. Indeed, the multiuser scheduling algorithm can reduce the effect of the Doppler spread if it exploits the information of temporal correlation appropriately. However, the effect of spatial correlation can be minimized if the antenna spacing is sufficient in rich scattering MIMO channels regardless of the multiuser scheduling algorithm used.